Classification of Digital Modulation Schemes Using Linear and Nonlinear Classifiers

Abstract

The potential benefits of automated detection of digital modulation types have made it a continuing topic of research for many years. Commercial systems could be made more interoperable and military sensors could send demodulated products for analysis, to name just two. Noisy channels and multipath fading environments continue to make this a challenging problem. This thesis applies classification algorithms that have been used in other applications. Nine different digital modulation schemes are considered. The criteria for selecting higher-ordered moments and cumulants as features for discrimination are discussed. An overview of the classification algorithms considered is provided, as well as the statistical models for noisy channels. Results show that the scheme proposed here works well in AWGN channels and in moderate fading conditions.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2010
Accession Number
ADA518653

Entities

People

  • Nathan P. Geisinger

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Amplitude Modulation
  • Communication Systems
  • Computational Science
  • Computers
  • Data Science
  • Digital Communications
  • Dimensionality Reduction
  • Doppler Effect
  • Electrical Engineering
  • Frequency Shift
  • Information Science
  • Machine Learning
  • Modulation
  • Multiple Access
  • Random Variables
  • Supervised Machine Learning

Fields of Study

  • Engineering

Readers

  • Computer Vision.
  • Radar Systems Engineering.
  • Systems Analysis and Design